brown_warner_1980: Brown and Warner parametric test (1980).
In estudy2: An Implementation of Parametric and Nonparametric Event Study

Description Usage Arguments Details Value References See Also Examples

An event study parametric test described in Brown and Warner 1980.

1	brown_warner_1980(list_of_returns, event_start, event_end)

`list_of_returns`	a list of objects of S3 class `returns`, each element of which is treated as a security.
`event_start`	an object of `Date` class giving the first date of the event period.
`event_end`	an object of `Date` class giving the last date of the event period.

Performs a parametric test for the event study, which is described in Brown and Warner 1980. The test assumes a cross-sectional independence and an insignificance of event-induced variance. The test examines the hypothesis whether the theoretical cross-sectional expected value for a given day is equal to zero. The standard deviation in statistics is calculated as the cross-sectional mean of companies' variances, estimated on the estimation period. It calculates statistics even if the event window and the estimation period are overlapped (intersect). The critical values are Student's t-distributed (no approximation in limit). The significance levels of α are 0.1, 0.05, and 0.01 (marked respectively by *, **, and ***). It was designed to measure monthly data: for daily data look at Brown and Warner 1985 and brown_warner_1985.

A data frame of the following columns:

date: a calendar date
weekday: a day of the week
percentage: a share of non-missing observations for a given day
mean: an average abnormal return
bw_1980_stat: a Brown and Warner (1980) test statistic
bw_1980_signif: a significance of the statistic

Brown S.J., Warner J.B. Measuring security price performance. Journal of Financial Economics, 8:205-258, 1980.

parametric_tests, brown_warner_1985, t_test, patell, boehmer, and lamb.

## Not run: 
library("magrittr")
rates_indx <- get_prices_from_tickers("^GSPC",
                                      start = as.Date("2019-04-01"),
                                      end = as.Date("2020-04-01"),
                                      quote = "Close",
                                      retclass = "zoo") %>%
    get_rates_from_prices(quote = "Close",
                          multi_day = TRUE,
                          compounding = "continuous")
tickers <- c("AMZN", "ZM", "UBER", "NFLX", "SHOP", "FB", "UPWK")
get_prices_from_tickers(tickers,
                        start = as.Date("2019-04-01"),
                        end = as.Date("2020-04-01"),
                        quote = "Close",
                        retclass = "zoo") %>%
    get_rates_from_prices(quote = "Close",
                          multi_day = TRUE,
                          compounding = "continuous") %>%
    apply_market_model(regressor = rates_indx,
                       same_regressor_for_all = TRUE,
                       market_model = "sim",
                       estimation_method = "ols",
                       estimation_start = as.Date("2019-04-01"),
                       estimation_end = as.Date("2020-03-13")) %>%
    brown_warner_1980(event_start = as.Date("2020-03-16"),
                      event_end = as.Date("2020-03-20"))

## End(Not run)
## The result of the code above is equivalent to:
data(securities_returns)
brown_warner_1980(list_of_returns = securities_returns,
                  event_start = as.Date("2020-03-16"),
                  event_end = as.Date("2020-03-20"))